MICRONITE is like having a smart decision maker, most experienced operator, and engineer on duty 24 hours a day.
Model Predictive Control reduces variability of key features, increases yield, and maximizes throughput and profit by moving the process to an optimal state of control.
Consolidated quality control and tool change prediction.
Bars are historical tool-life data. Diamonds are predictive tool life.
Tool Life Histograms
Advanced methodology of tool life management
Step 1. Automatically monitor tool life and causes of its termination for all roughing and finishing tools
Step 2. Maximize tool life using applied predictive models. Follow MICRONITE’s decisions on tool changeovers.
Step 3. Establish statistical tool life baselines and select type of adaptive or fixed tool control model which includes tooling and inspection data
Step 4. Initiate tool-and-process optimization using feedback from continuous process monitoring
Increase of tool-life longevity comes from MICRONITE’s machining knowledge
- Get reliable, up-to-date tooling data to guide every process improvement decision
- Control, analyze, and increase life of critical tools
- Get early-warning signals on tool under-performance
- Conduct efficient root-cause analyses with powerful filtering capabilities
- Make operations super-efficient by running with minimum tool changes
- Automatic downtime data capture
- Paperless operation timelines
- Timed equipment and labor data
- Real-time production analytics
- Management team effectiveness
- Solutions for downtime reduction
- Non-conformance cause analysis
The effectiveness of direct machine-MICRONITE interface
- Automated control of production schedule and product quality
- Run time interfaces for single operations
- Run-time interfaces for open work orders
- Automated certification of equipment-related production effectiveness
- Time-based Overall Production Effectiveness, Overall Machining Performance, O.E.E. and derivatives
- Throughput-based fractional and total machining effectiveness
- Operator performance tracking
- Measurement of gains in productivity and quality
- Technological innovations
- Cross-functional team building
- Discovery and model-based analysis of causes of loss in productivity and quality
- Development of analytical background for proactive maintenance
MICRONITE makes it so the user is able to pinpoint and eliminate all causes of inferior machine capability long before any mechanical symptoms become evident, this is the advantage of proactive maintenance over predictive maintenance. Proactive maintenance is directed by MICRONITE with discovery of departure from a normal quality output and lining up simple tests aimed at the sources of deviations. MICRONITE is designed to take timely and accurate actions as oppose to (1) making repairs when often nothing is broken and (2) accommodating the underperformance of equipment as normal and routine.
The first step to proactive maintenance is MICRONITE’s monitoring of the dynamics on a sample variation (machine precision) and MICRONITE-computed capability to hold the closest tolerances. The second step is arrangement of the inspection matrix for the engineering study of conditions and equipment components including fixtures, spindles, tool holders, etc. The third step is performed by MICRONITE using automated data analysis and decisions to accept or reject contribution of particular component into cumulative process capability. With rigid MICRONITE practices, the machine will be running at the highest level of efficiency.